The 'make it stick' section is where most consulting engagements fall apart. It's easy to design a solution. It's much harder to change how people actually behave day to day. The habit, incentive, and support structure piece requires staying involved longer than most scopes of work allow. The consultants who build that into their engagements from the start tend to get the repeat work.
My fav part: "Clients want someone who can define what success looks like, diagnose what’s really going wrong, design solutions that fit their reality, and stay involved long enough to make the change stick." Thanks for this reminder- great framework!
A great post, and one that's clearly based on years of experience of actually doing the work.
I get frustrated when I see advertised roles described as 'consultant' when they are actually for project resources who won't be doing any of this type of work.
I love the breakdown in the graphic on client offers. Consulting and advising are too often confused or used interchangeably. And I think that's a key reason why clients often don't feel they get value from hiring a consultant.
I've often found that a lot of the stress and issues that arise in client/consultant relationships arise from a failure to constantly clarify expectations
I can never overstate the importance of Step 2 on elaborating the appropriate problem statement.
Too many consultants, even experienced ones, do a poor job there, jump into solution mode too early, and end up solving an adjacent problem but not the right one!
I think it's so tempting to try and start working on the solution before fully exploring the problem - and the potential additional opportunities that creates.
Love the framework Richard. I am enjoying overlaying the AI enablers for various aspects of your framework to define a hybrid data model that ensures we can weave the AI enablement that is deprecating human aspects but cannot ever replace the human elements that will always be needed based on context, like judgement, trust, and empathy.
Hi, Richard. Yeah, I think everybody's trying to balance where AI makes sense and where it can either be risky or does not have the context to properly serve its purpose. For what it's worth, I created a matrix to try to navigate the various consulting activities. And there's really two dimensions. One is, what's the cost of making a mistake, which is consequence. And the second is, how much does the AI need to know about my particular situation and nuance, which I call context. This is a baseline, but certainly not completely foolproof guide to trying to navigate where AI makes sense and where human oversight or curation is needed. https://substack.com/home/post/p-180750351
The 'make it stick' section is where most consulting engagements fall apart. It's easy to design a solution. It's much harder to change how people actually behave day to day. The habit, incentive, and support structure piece requires staying involved longer than most scopes of work allow. The consultants who build that into their engagements from the start tend to get the repeat work.
Completely agree - I think it's easiest the hardest part - yet also the area that gets discussed the least.
My fav part: "Clients want someone who can define what success looks like, diagnose what’s really going wrong, design solutions that fit their reality, and stay involved long enough to make the change stick." Thanks for this reminder- great framework!
thank you! I really hope it helps!
Mine too, this statement nails it
A great post, and one that's clearly based on years of experience of actually doing the work.
I get frustrated when I see advertised roles described as 'consultant' when they are actually for project resources who won't be doing any of this type of work.
Thanks Nicole - really glad it helps.
I think 'consultant' is used by a lot of organisations as a workaround to not add headcount . It was common when I worked at the UN back in the day.
Thank you Richard, a great points that giving value to readers.
Thanks Robert - appreciate the feedback!
The evaluation step is the real differentiator most consultants stop at delivery, not results.
If you can tie work to measurable impact, you move from “advisor” to “indispensable.”
This is absolute gold. Thanks for sharing!
Thank you - really hope it helps!
Thanks for the article. I have always dealt with scope creep. Clients need consultants to show them the future.
thanks for resharing it - much appreciated!
I love the breakdown in the graphic on client offers. Consulting and advising are too often confused or used interchangeably. And I think that's a key reason why clients often don't feel they get value from hiring a consultant.
Thanks Neema :-)
Great read! I appreciate that you stress constant clarification. It carries through the entire process.
I've often found that a lot of the stress and issues that arise in client/consultant relationships arise from a failure to constantly clarify expectations
Excellent framework, Richard.
I can never overstate the importance of Step 2 on elaborating the appropriate problem statement.
Too many consultants, even experienced ones, do a poor job there, jump into solution mode too early, and end up solving an adjacent problem but not the right one!
Thanks - completely agree!
I think it's so tempting to try and start working on the solution before fully exploring the problem - and the potential additional opportunities that creates.
Love the framework Richard. I am enjoying overlaying the AI enablers for various aspects of your framework to define a hybrid data model that ensures we can weave the AI enablement that is deprecating human aspects but cannot ever replace the human elements that will always be needed based on context, like judgement, trust, and empathy.
Thanks Chris - curious to see what you can come up with here - anything you can share?
Hi, Richard. Yeah, I think everybody's trying to balance where AI makes sense and where it can either be risky or does not have the context to properly serve its purpose. For what it's worth, I created a matrix to try to navigate the various consulting activities. And there's really two dimensions. One is, what's the cost of making a mistake, which is consequence. And the second is, how much does the AI need to know about my particular situation and nuance, which I call context. This is a baseline, but certainly not completely foolproof guide to trying to navigate where AI makes sense and where human oversight or curation is needed. https://substack.com/home/post/p-180750351